Search results for: compressive strength prediction

Authors: A. Falsafi, M. Dadkhah, S. Shahidi

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The destruction and defeat of drill pipes and drill rigs in oil wells often combined with a combination of shear modulus II and III. In such a situation, the strength and load bearing capacity of the drill are evaluated based on the principles of fracture mechanics and crack growth criteria. In this paper, using the three-dimensional stress equations around the Turkish frontier, the relations of the tense-tense criterion (MTS) are extracted for the loading of the combined II and III modulus. It is shown that in crisp deflection under loading of combination II and III, the level of fracture is characterized by two different angles: the longitudinal angle of deflection θ and the angle of the deflection of the alpha. Based on the relationships obtained from the MTS criterion, the failure criteria, the longitudinal angle of the theta failure and the lateral angle of the failure of the alpha are presented. Also, the role of Poisson's coefficient on these parameters is investigated in these graphs.

Keywords: most tangential tension criterion, longitudinal angle of failure, side angle of fracture, drills crack

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Authors: Francisco Reyes, Hector Ramirez

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In the coastal zones are home to mangrove swamps, coral reefs, and seagrass ecosystems, which are the most biodiverse and fragile on the planet. These areas support a great diversity of marine life; they are also extraordinarily important for humans in the provision of food, water, wood, and other associated goods and services; they also contribute to climate regulation. The lack of an automated model that generates information on the dynamics of changes in coastlines and coastal erosion is identified as a central problem. Coastlines were determined from 1984 to 2020 on the Google Earth platform Engine from Landsat and Sentinel images, using the Normalized Differential Water Index (MNDWI) and Digital Shoreline Analysis System (DSAS) v5.0. Starting from the 2020 coastline, the 10-year prediction (Year 2031) was determined with the erosion of 238.32 hectares and an accretion of 181.96 hectares, while the 20-year prediction (Year 2041) will be presented an erosion of 544.04 hectares and an accretion of 133.94 hectares. The erosion and accretion of Playa Muelle in the municipality of Puerto Colombia were established, which will register the highest value of erosion. The coverage that presented the greatest change was that of artificialized Territories.

Keywords: coastline, coastal erosion, MNDWI, Google Earth Engine, Colombia

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Authors: Firas Al-Mahmoud, Jean-Michel Mechling, Mohamed Shaban

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The long-term durability of fibre reinforced polymer (FRP) composites is often stated as being the main reason for the use of these materials. Indeed, structures externally or Near Surface Mounted (NSM) reinforced with Carbon Fibre Reinforcement Polymer CFRP are often in contact with temperature cycles and salt water immersion and other environmental conditions that reduce the expected durability of the system. Bond degradation is a frequent cause of premature failure of structural elements and environmental conditions are known to relate to such failures. The purpose of this study is to investigate the effect of environmental exposure on the bond for different CFRP strengthening systems. Bending tests were conducted to evaluate the bond with and without environmental exposure. The specimens were strengthened with CFRP sheets, CFRP plates and NSM CFRP rods embedded in two filling materials: epoxy resin and mortar. Then, they were exposed to up to 300 freeze–thaw cycles. One freeze–thaw cycle consisted of four stages according to ASTM or immersed in 3.5% salted tap water. A total of thirty-six specimens were prepared for this purpose. Results showed a decrease in ultimate bond strength for specimens strengthened by CFRP sheets that were immersed in salt water for 120 days, while a reduction was shown for CFRP sheet and plate bonded specimens that were subjected to 300 freeze–thaw cycles. Exposing NSM CFRP rod strengthened specimens, embedded in resin or mortar, to freeze–thaw cycles or to immersion in salt water does not affect the bond strength.

Keywords: durability, strengthening, FRP, bond, freeze–thaw

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Authors: Abbas Vahedian, Rijun Shrestha, Keith Crews

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In recent years, fibre reinforced polymers as applications of strengthening materials have received significant attention by civil engineers and environmentalists because of their excellent characteristics. Currently, these composites have become a mainstream technology for strengthening of infrastructures such as steel, concrete and more recently, timber and masonry structures. However, debonding is identified as the main problem which limit the full utilisation of the FRP material. In this paper, a preliminary analysis of factors affecting bond strength of FRP-to-concrete and timber bonded interface has been conducted. A novel theoretical method through regression analysis has been established to evaluate these factors. Results of proposed model are then assessed with results of pull-out tests and satisfactory comparisons are achieved between measured failure loads (R² = 0.83, P < 0.0001) and the predicted loads (R² = 0.78, P < 0.0001).

Keywords: debonding, fibre reinforced polymers (FRP), pull-out test, stepwise regression analysis

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Authors: K. Shahril, A. Nizam, M. Sabri, A. Siti Rohana, H. Salmah

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Chemical modifier (Acrylic Acid) is used as filler treatment to improve mechanical properties and swelling behavior of polypropylene/coconut fiber (PP/CF) composites by creating more adherent bonding between CF filler and PP Matrix. Treated (with chemical modifier) and untreated (without chemical modifier) composites were prepared in the formulation of 10 wt%, 20 wt%, 30 wt%, and 40 wt%. The mechanical testing indicates that composite with 10 wt% of untreated composite has the optimum value of tensile strength, and the composite with chemical modifier shows the tensile strength was increased. By increasing of filler loading, elastic modulus was increased while the elongation at brake was decreased. Meanwhile, the swelling test discerned that the increase of filler loading increased the water absorption of composites and the presence of chemical modifier reduced the equilibrium water absorption percentage.

Keywords: coconut fiber, polypropylene, acid acrylic, ethanol, chemical modifier, composites

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Chetra Mang, Ahmadali Tahmasebimoradi, Xavier Lorang

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Lattice structures are widely used in various applications, especially in aeronautic, aerospace, and medical applications because of their high performance properties. Thanks to advancement of the additive manufacturing technology, the lattice structures can be manufactured by different methods such as laser beam melting technology. However, the presence of geometric defects in the lattice structures is inevitable due to the manufacturing process. The geometric defects may have high impact on the mechanical strength of the structures. This work analyzes the correlation between the manufacturing parameters and the mechanical strengths of the lattice structures. To do that, two types of the lattice structures; body-centered cubic with z-struts (BCCZ) structures made of Inconel718, and body-centered cubic (BCC) structures made of Scalmalloy, are manufactured by laser melting beam machine using Taguchi design of experiment. Each structure is placed on the substrate with a specific position and orientation regarding the roller direction of deposed metal powder. The position and orientation are considered as the manufacturing parameters. The geometric defects of each beam in the lattice are characterized and used to build the geometric model in order to perform simulations. Then, the mechanical strengths are defined by the homogeneous response as Young's modulus and yield strength. The distribution of mechanical strengths is observed as a function of manufacturing parameters. The mechanical response of the BCCZ structure is stretch-dominated, i.e., the mechanical strengths are directly dependent on the strengths of the vertical beams. As the geometric defects of vertical beams are slightly changed based on their position/orientation on the manufacturing substrate, the mechanical strengths are less dispersed. The manufacturing parameters are less influenced on the mechanical strengths of the structure BCCZ. The mechanical response of the BCC structure is bending-dominated. The geometric defects of inclined beam are highly dispersed within a structure and also based on their position/orientation on the manufacturing substrate. For different position/orientation on the substrate, the mechanical responses are highly dispersed as well. This shows that the mechanical strengths are directly impacted by manufacturing parameters. In addition, this work is carried out to study the uncertainty propagation of the geometric defects on the mechanical strength of the BCC lattice structure made of Scalmalloy. To do that, we observe the distribution of mechanical strengths of the lattice according to the distribution of the geometric defects. A probability density law is determined based on a statistical hypothesis corresponding to the geometric defects of the inclined beams. The samples of inclined beams are then randomly drawn from the density law to build the lattice structure samples. The lattice samples are then used for simulation to characterize the mechanical strengths. The results reveal that the distribution of mechanical strengths of the structures with the same manufacturing parameters is less dispersed than one of the structures with different manufacturing parameters. Nevertheless, the dispersion of mechanical strengths due to the structures with the same manufacturing parameters are unneglectable.

Keywords: geometric defects, lattice structure, mechanical strength, uncertainty propagation

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Authors: Ahmad Idris, Armaya`u Suleiman Labo, Ado Yusuf Abdulfatah, Murtala Umar

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Super pave is the short form of Superior Performing Asphalt Pavement and represents a basis for specifying component materials, asphalt mixture design and analysis, and pavement performance prediction. This new technology is the result of long research projects conducted by the strategic Highway Research program (SHRP) of the Federal Highway Administration. This research was aimed at examining the suitability of Aggregates found in Kano for used in super pave design method. Aggregates samples were collected from different sources in Kano Nigeria and their Engineering properties, as they relate to the SUPERPAVE design requirements were determined. The average result of Coarse Aggregate Angularity in Kano was found to be 87% and 86% of one fractured face and two or more fractured faces respectively with a standard of 80% and 85% respectively. Fine Aggregate Angularity average result was found to be 47% with a requirement of 45% minimum. A flat and elongated particle which was found to be 10% has a maximum criterion of 10%. Sand equivalent was found to be 51% with the criteria of 45% minimum. Strength tests were also carried out, and the results reflect the requirements of the standards. The tests include Impact value test, Aggregate crushing value and Aggregate Abrasion tests and the results are 27.5%, 26.7% and 13% respectively with a maximum criteria of 30%. Specific gravity was also carried out and the result was found to have an average value of 2.52 with a criterion of 2.6 to 2.9 and Water absorption was found to be 1.41% with maximum criteria of 0.6%. From the study, the result of the tests indicated that the aggregates properties have met the requirements of Super pave design method based on the specifications of ASTMD 5821, ASTM D 4791, AASHTO T176, AASHTO T33 and BS815.

Keywords: aggregates, construction, road design, super pave

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Authors: M. Alsaadi, A. Erkliğ, M. Bulut

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This paper experimentally investigates the flexural and tensile properties of the industrial wastes sewage sludge ash (SSA) and fly ash (FA), and conventional ceramic powder silicon carbide (SiC) filled polyester composites. Four weight fractions (5, 10, 15 and 20 wt%) for each micro filler were used for production of composites. Then, test samples were produced according to ASTM. The resulting degree of particle dispersion in the polymer matrix was visualized by using scanning electron microscope (SEM). Results from this study showed that the tensile strength increased up to its maximum value at filler content 5 wt% of SSA, FA and SiC. Flexural strength increased with addition of particulate filler up to its maximum value at filler content 5 wt% of SSA and FA while for SiC decreased for all weight fractions gradually. The addition of SSA, FA and SiC fillers resulted in increase of tensile and flexural modulus for all the particulate composites. Industrial waste SSA can be used as an additive with polymer to produce composite materials.

Keywords: particle-reinforcement, sewage sludge ash, polymer matrix composites, mechanical properties

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Authors: Ki-Seok Kwon, Heung-Youl Kim

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This research evaluated fire resistances of high-strengthened reinforced concrete (RC) column, spiral wire rope which applied with 60, and 100MPa. The fire resistance test of RC column with loading condition was conducted following the ISO 834 (3 hours). This experiment set mixing of fiber (PP fiber, Steel fiber) and types of horizontal reinforcement as a variable of reinforcement method. The fire resistance test measured the main steel bar’s max and mean temperatures also the shrinkage and shrinking ratio of columns(500 X 500 X 3,000mm) with loadings. As a result, the specimen of 60MPa attained three hours fire resistance with only spiral wire rope. Also, the specimen of 100MPa must be reinforced with fibers and spiral wire rope to attain three hours fire resistance.

Keywords: reinforced concrete column, high strength concrete, wire rope, fire resistance test

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The PUSPATI TRIGA Reactor (RTP), Malaysia reached its first criticality on June 28, 1982, with power capacity 1MW thermal. The Feedback Control Algorithm (FCA) which is conventional Proportional-Integral (PI) controller, was used for present power control method to control fission process in RTP. It is important to ensure the core power always stable and follows load tracking within acceptable steady-state error and minimum settling time to reach steady-state power. At this time, the system could be considered not well-posed with power tracking performance. However, there is still potential to improve current performance by developing next generation of a novel design nuclear core power control. In this paper, the dual-mode predictions which are proposed in modelling Optimal Model Predictive Control (OMPC), is presented in a state-space model to control the core power. The model for core power control was based on mathematical models of the reactor core, OMPC, and control rods selection algorithm. The mathematical models of the reactor core were based on neutronic models, thermal hydraulic models, and reactivity models. The dual-mode prediction in OMPC for transient and terminal modes was based on the implementation of a Linear Quadratic Regulator (LQR) in designing the core power control. The combination of dual-mode prediction and Lyapunov which deal with summations in cost function over an infinite horizon is intended to eliminate some of the fundamental weaknesses related to MPC. This paper shows the behaviour of OMPC to deal with tracking, regulation problem, disturbance rejection and caters for parameter uncertainty. The comparison of both tracking and regulating performance is analysed between the conventional controller and OMPC by numerical simulations. In conclusion, the proposed OMPC has shown significant performance in load tracking and regulating core power for nuclear reactor with guarantee stabilising in the closed-loop.

Keywords: core power control, dual-mode prediction, load tracking, optimal model predictive control

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Authors: Adeniran K. Ademuwagun, Alastair Allen

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The relationship dependence between RSS and distance in an enclosed environment is an important consideration because it is a factor that can influence the reliability of any localization algorithm founded on RSS. Several algorithms effectively reduce the variance of RSS to improve localization or accuracy performance. Our proposed algorithm essentially avoids this pitfall and consequently, its high adaptability in the face of erratic radio signal. Using 3 anchors in close proximity of each other, we are able to establish that RSS can be used as reliable indicator for localization with an acceptable degree of accuracy. Inherent in this concept, is the ability for each prospective anchor to validate (guarantee) the position or the proximity of the other 2 anchors involved in the localization and vice versa. This procedure ensures that the uncertainties of radio signals due to multipath effects in enclosed environments are minimized. A major driver of this idea is the implicit topological relationship among sensors due to raw radio signal strength. The algorithm is an area based algorithm; however, it does not trade accuracy for precision (i.e the size of the returned area).

Keywords: anchor nodes, centroid algorithm, communication graph, radio signal strength

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Authors: Arnab Majumdar, Sanjoy Sadhukhan

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Although gun barrel steels are an important variety from defense view point, available literatures are very limited. In the present work, an IF grade Ni-Cr-Mo-V high strength low alloy steel is produced in Electric Earth Furnace-ESR Route. Ingot was hot forged to desired dimension with a reduction ratio of 70-75% followed by homogenization, hardening and tempering treatment. Sample chemistry, NMIR, macro and micro structural analyses were done. Mechanical properties which include tensile, impact, and fracture toughness were studied. Ultrasonic testing was done to identify internal flaws. The existing high strength low alloy Ni-Cr-Mo-V steel shows improved properties in modified processing route and heat treatment schedule in comparison to properties noted earlier for manufacturing of gun barrels. The improvement in properties seems to withstand higher explosive loads with the same amount of steel in gun barrel application.

Keywords: gun barrel steels, IF grade, chemistry, physical properties, thermal and mechanical processing, mechanical properties, ultrasonic testing

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Authors: Christoph Ostermair

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We deal with the effect of correlation between prospects on human decision making under uncertainty as proposed by the comparatively new and promising model of “salience theory of choice under risk”. In this regard, we show that the theory entails the prediction that the inconsistency of choices, known as the Allais paradox, should not be an issue in the context of “real-life decision making”, which typically corresponds to situations of subjective uncertainty. The Allais paradox, probably the best-known anomaly regarding expected utility theory, would then essentially have no practical relevance. If, however, empiricism contradicts this prediction, salience theory might suffer a serious setback. Explanations of the model for variable human choice behavior are mostly the result of a particular mechanism that does not come to play under perfect correlation. Hence, if it turns out that correlation between prospects – as typically found in real-world applications – does not influence human decision making in the expected way, this might to a large extent cost the theory its explanatory power. The empirical literature regarding the Allais paradox under subjective uncertainty is so far rather moderate. Beyond that, the results are hard to maintain as an argument, as the presentation formats commonly employed, supposably have generated so-called event-splitting effects, thereby distorting subjects’ choice behavior. In our own incentivized experimental study, we control for such effects by means of two different choice settings. We find significant event-splitting effects in both settings, thereby supporting the suspicion that the so far existing empirical results related to Allais paradoxes under subjective uncertainty may not be able to answer the question at hand. Nevertheless, we find that the basic tendency behind the Allais paradox, which is a particular switch of the preference relation due to a modified common consequence, shared by two prospects, is still existent both under an event-splitting and a coalesced presentation format. Yet, the modal choice pattern is in line with the prediction of salience theory. As a consequence, the effect of correlation, as proposed by the model, might - if anything - only weaken the systematic choice pattern behind the Allais paradox.

Keywords: Allais paradox, common consequence effect, models of decision making under risk and uncertainty, salience theory

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Authors: Seok Hong Min, Tae Kwon Ha

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High strength Fe-36Ni-base Invar alloys containing Al contents up to 0.3 weight percent were cast into ingots and thermodynamic equilibrium during solidification has been investigated in this study. From the thermodynamic simulation using Thermo-Calc®, it has been revealed that equilibrium phases which can be formed are two kinds of MC-type precipitates, MoC, and M2C carbides. The mu phase was also expected to form by addition of aluminum. Microstructure observation revealed the coarse precipitates in the as-cast ingots, which was non-equilibrium phase and could be resolved by the successive heat treatment. With increasing Al contents up to 0.3 wt.%, tensile strength of Invar alloy increased as 1400MPa after cold rolling and thermal expansion coefficient increased significantly. Cold rolling appeared to dramatically decrease thermal expansion coefficient.

Keywords: invar alloy, aluminum, phase equilibrium, thermal expansion coefficient, microstructure, tensile properties

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

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Authors: Serge Mudinga Lemika, Samuel Olukayode Akinwamide, Aribo Sunday, Babatunde Abiodun Obadele, Peter Apata Olubambi

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Use of Duplex stainless steel has become predominant in applications where excellent corrosion resistance is of utmost importance. Corrosion behavior of duplex stainless steel induced with varying stress in a chloride media were studied. Characterization of as received 2205 duplex stainless steels were carried out to reveal its structure and properties tensile sample produced from duplex stainless steel was initially subjected to tensile test to obtain the yield strength. Stresses obtained by various percentages (20, 40, 60 and 80%) of the yield strength was induced in DSS samples. Corrosion tests were carried out in magnesium chloride solution at room temperature. Morphologies of cracks observed with optical and scanning electron microscope showed that samples induced with higher stress had its austenite and ferrite grains affected by pitting.

Keywords: duplex stainless steel, hardness, nanoceramics, spark plasma sintering

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Authors: Doaa H. Elgohary, Dina M. Hamoda, S. Yahia

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Technical textiles refer to textile materials that are engineered and designed to have specific functionalities and performance characteristics beyond their traditional use as apparel or upholstery fabrics. These textiles are usually developed for their unique properties such as strength, durability, flame retardancy, chemical resistance, waterproofing, insulation and other special properties. The development and use of technical textiles are constantly evolving, driven by advances in materials science, manufacturing technologies and the demand for innovative solutions in various industries. Kevlar 29 is a type of aramid fiber developed by DuPont. It is a high-performance material known for its exceptional strength and resistance to impact, abrasion, and heat. Kevlar 29 belongs to the Kevlar family, which includes different types of aramid fibers. Kevlar 29 is primarily used in applications that require strength and durability, such as ballistic protection, body armor, and body armor for military and law enforcement personnel. It is also used in the aerospace and automotive industries to reinforce composite materials, as well as in various industrial applications. Two different Kevlar samples were used coated with cooper lithium silicate (CLS); ten different mechanical and physical properties (weight, thickness, tensile strength, elongation, stiffness, air permeability, puncture resistance, thermal conductivity, stiffness, and spray test) were conducted to approve its functional performance efficiency. The influence of different mechanical properties was statistically analyzed using an independent t-test with a significant difference at P-value = 0.05. The radar plot was calculated and evaluated to determine the best-performing samples. The results of the independent t-test observed that all variables were significantly affected by yarn counts except water permeability, which has no significant effect. All properties were evaluated for samples 1 and 2, a radar chart was used to determine the best attitude for samples. The radar chart area was calculated, which shows that sample 1 recorded the best performance, followed by sample 2. The surface morphology of all samples and the coating materials was determined using a scanning electron microscope (SEM), also Fourier Transform Infrared Spectroscopy Measurement for the two samples.

Keywords: cooper lithium silicate, independent t-test, kevlar, technical textiles.

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Authors: Nato Kutaladze, George Mikuchadze, Giorgi Sokhadze

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Precipitation forecasts are one of the most demanding applications in numerical weather prediction (NWP). Georgia, as the whole Caucasian region, is characterized by very complex topography. The country territory is prone to flash floods and mudflows, quantitative precipitation estimation (QPE) and quantitative precipitation forecast (QPF) at any leading time are very important for Georgia. In this study, advanced research weather forecasting model’s skill in QPF is investigated over Georgia’s territory. We have analyzed several convection parameterization and microphysical scheme combinations for different rainy episodes and heavy rainy phenomena. We estimate errors and biases in accumulated 6 h precipitation using different spatial resolution during model performance verification for 12-hour and 24-hour lead time against corresponding rain gouge observations and satellite data. Various statistical parameters have been calculated for the 8-month comparison period, and some skills of model simulation have been evaluated. Our focus is on the formation and organization of convective precipitation systems in a low-mountain region. Several problems in connection with QPF have been identified for mountain regions, which include the overestimation and underestimation of precipitation on the windward and lee side of the mountains, respectively, and a phase error in the diurnal cycle of precipitation leading to the onset of convective precipitation in model forecasts several hours too early.

Keywords: extremal dependence index, false alarm, numerical weather prediction, quantitative precipitation forecasting

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Authors: Derradji Chebli, Abdallah Bouguettoucha, Abdelbaki Reffas Khalil Guediri, Abdeltif Amrane

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The removal of Methyl Green dye (MG) from aqueous solutions using modified P-brutia cones (PBH and PBN), has been investigated work. The physical parameters such as pH, temperature, initial MG concentration, ionic strength are examined in batch experiments on the sorption of the dye. Adsorption removal of MG was conducted at natural pH 4.5 because the dye is only stable in the range of pH 3.8 to 5. It was observed in experiments that the P-brutia cones treated with NaOH (PBN) exhibited high affinity and adsorption capacity compared to the MG P-brutia cones treated with HCl (PBH) and biosorption capacity of modified P-brutia cones (PBN and PBH) was enhanced by increasing the temperature. This is confirmed by the thermodynamic parameters (ΔG° and ΔH°) which show that the adsorption of MG was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase in the randomness for both adsorbent (PBN and PBH) during the adsorption process. The kinetic model pseudo-first order, pseudo-second order, and intraparticle diffusion coefficient were examined to analyze the sorption process; they showed that the pseudo-second-order model is the one that best describes the adsorption process (MG) on PBN and PBH with a correlation coefficient R²> 0.999. The ionic strength has shown that it has a negative impact on the adsorption of MG on two supports. A reduction of 68.5% of the adsorption capacity for a value Ce=30 mg/L was found for the PBH, while the PBN did not show a significant influence of the ionic strength on adsorption especially in the presence of NaCl. Among the tested isotherm models, the Langmuir isotherm was found to be the most relevant to describe MG sorption onto modified P-brutia cones with a correlation factor R²>0.999. The capacity adsorption of P-brutia cones, was confirmed for the removal of a dye, MG, from aqueous solution. We note also that P-brutia cones is a material very available in the forest and low-cost biomaterial

Keywords: adsorption, p-brutia cones, forest wastes, dyes, isotherm

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Authors: T. P. Sathishkumar, P. Navaneethakrishnan

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The research work investigates the variation of tensile properties for the sansevieria ehrenbergii fiber (SEF) and SEF reinforced polyester composites respect to various water absorption time. The experiments were conducted according to ATSM D3379-75 and ASTM D570 standards. The percentage of water absorption for composite specimens was measured according to ASTM D570 standard. The fiber of SE was cut in to 30 mm length for preparation of the composites. The simple hand lay-up method followed by compression moulding process adopted to prepare the randomly oriented SEF reinforced polyester composites at constant fiber weight fraction of 40%. The surface treatment was done on the SEFs with various chemicals such as NaOH, KMnO4, Benzoyl Peroxide, Benzoyl Chloride and Stearic Acid before preparing the composites. NaOH was used for pre-treatment of all other chemical treatments. The morphology of the tensile fractured specimens studied using the Scanning Electron Microscopic. The tensile strength of the SEF and SEF reinforced polymer composites were carried out with various water absorption time such as 4, 8, 12, 16, 20 and 24 hours respectively. The result shows that the tensile strength was drop off with increase in water absorption time for all composites. The highest tensile property of raw fiber was found due to lowest moistures content. Also the chemical bond between the cellulose and cementic materials such as lignin and wax was highest due to lowest moisture content. Tensile load was lowest and elongation was highest for the water absorbed fibers at various water absorption time ranges. During this process, the fiber cellulose inhales the water and expands the primary and secondary fibers walls. This increases the moisture content in the fibers. Ultimately this increases the hydrogen cation and the hydroxide anion from the water. In tensile testing, the water absorbed fibers shows highest elongation by stretching of expanded cellulose walls and the bonding strength between the fiber cellulose is low. The load carrying capability was stable at 20 hours of water absorption time. This could be directly affecting the interfacial bonding between the fiber/matrix and composite strength. The chemically treated fibers carry higher load and lower elongation which is due to removal of lignin, hemicellulose and wax content. The water time absorption decreases the tensile strength of the composites. The chemically SEF reinforced composites shows highest tensile strength compared to untreated SEF reinforced composites. This was due to highest bonding area between the fiber/matrix. This was proven in the morphology at the fracture zone of the composites. The intra-fiber debonding was occurred by water capsulation in the fiber cellulose. Among all, the tensile strength was found to be highest for KMnO4 treated SEF reinforced composite compared to other composites. This was due to better interfacial bonding between the fiber-matrix compared to other treated fiber composites. The percentage of water absorption of composites increased with time of water absorption. The percentage weight gain of chemically treated SEF composites at 4 hours to zero water absorption are 9, 9, 10, 10.8 and 9.5 for NaOH, BP, BC, KMnO4 and SA respectively. The percentage weight gain of chemically treated SEF composites at 24 hours to zero water absorption 5.2, 7.3, 12.5, 16.7 and 13.5 for NaOH, BP, BC, KMnO4 and SA respectively. Hence the lowest weight gain was found for KMnO4 treated SEF composites by highest percentage with lowest water uptake. However the chemically treated SEF reinforced composites is possible materials for automotive application like body panels, bumpers and interior parts, and household application like tables and racks etc.

Keywords: fibres, polymer-matrix composites (PMCs), mechanical properties, scanning electron microscopy (SEM)

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Amir Doustgani

Abstract:

Melt electrospinning is a safe and simple technique for the production of micro and nanofibers which can be an alternative to conventional solvent electrospinning. The effects of various melt-electrospinning parameters, including molecular weight, electric field strength, flow rate and temperature on the morphology and fiber diameter of polylactic acid were studied. It was shown that molecular weight was the predominant factor in determining the obtainable fiber diameter of the collected fibers. An orthogonal design was used to examine process parameters. Results showed that molecular weight is the most effective parameter on the average fiber diameter of melt electrospun PLA nanofibers and the flow rate has the less important impact. Mean fiber diameter increased by increasing MW and flow rate, but decreased by increasing electric field strength and temperature. MFD of optimized fibers was below 100 nm and the result of software was in good agreement with the experimental condition.

Keywords: fiber formation, processing, spinning, melt blowing

Procedia PDF Downloads 436

Authors: Mahtab Abdollahi Sarvi, Siamak Epackachi, Ali Imanpour

Abstract:

Reinforced concrete shear walls are commonly used as the lateral load-resisting system of mid- to high-rise office or residential buildings around the world. Design of such systems is often governed by wind rather than seismic effects, in particular in low-to-moderate seismic regions. The current design philosophy as per the majority of building codes under wind loads require elastic response of lateral load-resisting systems including reinforced concrete shear walls when subjected to the rare design wind load, resulting in significantly large wall sections needed to meet strength requirements and drift limits. The latter can highly influence the design in upper stories due to stringent drift limits specified by building codes, leading to substantial added costs to the construction of the wall. However, such walls may offer limited to moderate over-strength and ductility due to their large reserve capacity provided that they are designed and detailed to appropriately develop such over-strength and ductility under extreme wind loads. This would significantly contribute to reducing construction time and costs, while maintaining structural integrity under gravity and frequently-occurring and less frequent wind events. This paper aims to investigate the over-strength and ductility capacity of several imaginary office buildings located in Edmonton, Canada with a glance at earthquake design philosophy. Selected models are 10- to 25-story buildings with three types of reinforced concrete shear wall configurations including rectangular, barbell, and flanged. The buildings are designed according to National Building Code of Canada. Then fiber-based numerical models of the walls are developed in Perform 3D and by conducting nonlinear static (pushover) analysis, lateral nonlinear behavior of the walls are evaluated. Ductility and over-strength of the structures are obtained based on the results of the pushover analyses. The results confirmed moderate nonlinear capacity of reinforced concrete shear walls under extreme wind loads. This is while lateral displacements of the walls pass the serviceability limit states defined in Pre standard for Performance-Based Wind Design (ASCE). The results indicate that we can benefit the limited nonlinear response observed in the reinforced concrete shear walls to economize the design of such systems under wind loads.

Keywords: concrete shear wall, high-rise buildings, nonlinear static analysis, response modification factor, wind load

Procedia PDF Downloads 103

Authors: Kriengsak Damampai, Skulrat Pichaiyut, Amit Das, Charoen Nacason

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The curing of epoxidized natural rubber (ENR) was performed by using metal ions (Ferric chloride, FeCl₃). Two different mole% of epoxide were used there are 25 mole% (ENR-25) and 50 mole% (ENR-50) epoxizied natural rubber. The main aim of this work was investigated the influence of metal ions on the coordination reaction of epoxidized natural rubber. Also, cure characteristics and mechanical properties of the rubber compounds were investigated. It was found that the ENR-50 compounds indicated superior modulus and tensile strength than the ENR-25 compounds. This was attributed to higher the cross-linking in the rubber via coordination linkages between the oxidation groups in ENR molecule and FeCl₃of metal ions. Various quantities of FeCl3 were also investigated. It is seen that the ENR-25 and 50 mole% compounds with FeCl₃ of more than 3 mmol exhibited higher modulus and tensile strength compare to the pure ENR. Furthermore, the FTIR spectra was used to confirm the cross-linked of ENR with FeCl₃.

Keywords: Epoxidized natural rubber, Ferric chloride, cross-linking, Coordination

Procedia PDF Downloads 77

Authors: Philip Baillie, Stuart W. Campbell, Alexander M. Galloway, Stephen R. Cater, Norman A. McPherson

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This study compared the mechanical and microstructural properties produced during friction stir welding(FSW) of S275 structural steel in air and underwater. Post weld tests assessed the tensile strength, micro-hardness, distortion, Charpy impact toughness and fatigue performance in each case. The study showed that there was no significant difference in the strength, hardness or fatigue life of the air and underwater specimens. However, Charpy impact toughness was shown to decrease for the underwater specimens and was attributed to a lower degree of recrystallization caused by the higher rate of heat loss experienced when welding underwater. Reduced angular and longitudinal distortion was observed in the underwater welded plate compared to the plate welded in air.

Keywords: Charpy impact toughness, distortion, fatigue, friction stir welding(FSW), micro-hardness, underwater

Procedia PDF Downloads 414

Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

Abstract:

The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

Procedia PDF Downloads 163

Authors: Balwinder Singh

Abstract:

Castings are produced by using aluminum alloy ADC 10 through the process of Ceramic Shell Investment Casting. Experiments are conducted as per the Taguchi L9 orthogonal array. In order to evaluate the effect of process parameters such as mould preheat temperature, preheat time, firing temperature and pouring temperature on surface roughness of ceramic shell investment castings, the Taguchi parameter design and optimization approach is used. Plots of means of significant factors and S/N ratios have been used to determine the best relationship between the responses and model parameters. It is found that the pouring temperature is the most significant factor. The best tensile strength of aluminum alloy ADC 10 is given by 150 ºC shell preheat temperature, 45 minutes preheat time, 900 ºC firing temperature, 650 ºC pouring temperature.

Keywords: investment casting, shell preheat temperature, firing temperature, Taguchi method

Procedia PDF Downloads 168

Authors: Onan Kilicaslan, Anil Kabaklarli, Levent Subasi, Erdem Bektas, Rifat Yilmaz

Abstract:

The Aluminum-Copper casting alloys are well known for their high mechanical strength, especially when compared to more commonly used Aluminum-Silicon alloys. A201 is one of the best in terms of strength vs. weight ratio among other aluminum alloys, which makes it suitable for premium quality casting applications in aerospace and automotive industries. It is reported that A201 has low castability, but it is easy to machine. However, there is a need to specifically determine the process window for feasible machining. This research investigates the machinability of A201 alloy after T7 heat treatment in terms of chip/burr formation, surface roughness, hardness, and microstructure. The samples are cast with low-pressure sand casting method and milling experiments are performed with uncoated carbide tools using different cutting speeds and feeds. Statistical analysis is used to correlate the machining parameters to surface integrity. It is found that there is a strong dependence of the cutting conditions on machinability and a process window is determined.

Keywords: A201-T7, machinability, milling, surface integrity

Procedia PDF Downloads 190